Deep learning image segmentation method and system based on edge feature extraction

Abstract

The invention discloses a deep learning image segmentation method and system based on edge feature extraction, and the system comprises an edge convolutional network which is used for extracting the edge features of an input image, and comprises a semantic edge convolutional network and an instance edge convolutional network, the semantic edge convolutional network processes background filling objects such as sky and roads in the image, and the instance edge convolutional network processes foreground instance objects such as figures and vehicles in the image; the feature extraction network comprises a same-side convolutional feature extraction network and a different-side convolutional feature extraction network, and the same-side convolutional feature extraction network realizes layer-by-layer extraction of features, retains feature attributes under different levels, and forms a complete feature level system; and according to the different-side convolution feature extraction network, cross-level feature fusion is realized through a connection method of changing a convolution structure and a shortcut, so that the learning potential of the feature extraction network is stimulated, and the feature extraction capability is improved.

Description

technical field [0001] The invention relates to the field of image segmentation in computer vision applications, in particular to a deep learning image segmentation method and system based on edge feature extraction. Background technique [0002] Image segmentation is a basic technology for scene understanding, and it plays a vital role in unmanned systems such as intelligent driving, autonomous navigation at the cognitive level of robots, drone landing systems, and intelligent security monitoring. The purpose of image segmentation is to divide each pixel in the image into a semantic category and an instance label, generate a global and unified segmented image, and realize pixel-level segmentation. The key to image segmentation is to identify the edge pixels of objects in the image and distinguish different objects, so the extraction of edge features is crucial to the image segmentation task. [0003] The traditional edge feature extraction method focuses on the texture gra...

AI Technical Summary

Problems solved by technology

The above networks use complex convolutional network structures to extract edge features by fusing features of different depths, which can easily cause a large increase in network calculations, resulting in low portability and difficult application of these methods.

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